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Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma
Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma
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Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma
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Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma
Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma

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Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma
Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma
Journal Article

Development and validation of a nomogram for predicting postoperative survival in patients with multifocal hepatocellular carcinoma

2025
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Overview
Background Hepatocellular carcinoma (HCC) is the fifth most common malignant tumor and the third leading cause of cancer-related death worldwide. Despite the significance of multifocality in HCC (M-HCC), most studies have predominantly treated it as a prognostic factor, lacking in-depth investigation into its prognostic implications. This retrospective study aims to integrate clinical and laboratory examinations to construct a predictive model that more accurately forecasts the prognosis of patients with M-HCC. This aims to guide personalized treatment strategies and improve overall survival rates. Methods We applied the Lasso and cross-validated Lasso (CV-Lasso) combined with Random Forest analysis to explore the prognostic factors influencing M-HCC. Simultaneously, we utilized the identified prognostic factors to construct a Nomogram. This Nomogram assigns scores based on the magnitude of the impact of each factor on prognosis, enabling the prediction of postoperative survival rates for patients. Subsequently, the model-derived risk scores categorized patients into low-risk and high-risk groups, and Kaplan–Meier curves were generated. Results The patients, who were enrolled, were divided into training and validation sets. Factors influencing the prognosis of M-HCC were identified through Lasso, cross-validated Lasso, and Random Forest analyses, revealing seven key factors: Age, Antiviral, Child–Pugh, Cirrhosis, White Blood Cell (WBC), Platelets (PLT), and Thrombin Time (TT). Nomograms were constructed based on these factors to predict 3-year, 5-year, and 8-year survival rates. ROC curves confirmed the predictive capability of various factors, with larger areas under the curve at 5 (AUC = 0.653) and 8 years (AUC = 0.733). Kaplan–Meier curves stratified patients into low-risk and high-risk groups, showing significantly higher survival times in the low-risk group (p < 0.0001). Conclusions Postoperative antiviral treatment for patients with M-HCC, aimed at enhancing immune function and protecting liver function, has been shown to extend patient survival. Simultaneously, factors such as Child–Pugh, age, and Cirrhosis in patients with M-HCC have been associated with a decrease in postoperative survival time.